Hierarchical Bayesian Approach To Reduce Uncertainty in the Aquatic Effect Assessment of Realistic Chemical Mixtures
| العنوان: | Hierarchical Bayesian Approach To Reduce Uncertainty in the Aquatic Effect Assessment of Realistic Chemical Mixtures |
|---|---|
| المؤلفون: | Ad M.J. Ragas, Rik Oldenkamp, Dik van de Meent, Harrie Hendriks |
| المساهمون: | RS-Research Line Learning (part of LIRS program), Department Science |
| المصدر: | Environmental Science & Technology, 49(17), 10457-10465. AMER CHEMICAL SOC Oldenkamp, R, Hendriks, H W M, van de Meent, D & Ragas, A M J 2015, ' Hierarchical Bayesian Approach To Reduce Uncertainty in the Aquatic Effect Assessment of Realistic Chemical Mixtures ', Environmental Science & Technology, vol. 49, no. 17, pp. 10457-10465 . https://doi.org/10.1021/acs.est.5b02651 Environmental Science and Technology, 49, 17, pp. 10457-10465 Environmental Science and Technology, 49, 10457-10465 |
| سنة النشر: | 2015 |
| مصطلحات موضوعية: | NOEC TOXICITY DATA, POTENTIALLY AFFECTED FRACTION, Bayesian probability, Antineoplastic Agents, ECOLOGICAL RISK, Chemical mixtures, Germany, ECOSYSTEMS, Environmental Chemistry, Sensitivity (control systems), Stochastics, MONITORING CONVERGENCE, Geography, Uncertainty, Environmental engineering, Bayes Theorem, General Chemistry, ECOTOXICOLOGY, SIMULATIONS, Anti-Bacterial Agents, Effect assessment, SPECIES-SENSITIVITY DISTRIBUTIONS, Aquatic environment, ECX, Stochastics and operational research, Environmental science, Biochemical engineering, RISK-ASSESSMENT, Water Pollutants, Chemical, Environmental Sciences |
| الوصف: | Species in the aquatic environment differ in their toxicological sensitivity to the various chemicals they encounter. In aquatic risk assessment, this interspecies variation is often quantified via species sensitivity distributions. Because the information available for the characterization of these distributions is typically limited, optimal use of information is essential to reduce uncertainty involved in the assessment. In the present study, we show that the credibility intervals on the estimated potentially affected fraction of species after exposure to a mixture of chemicals at environmentally relevant surface water concentrations can be extremely wide if a classical approach is followed, in which each chemical in the mixture is considered in isolation. As an alternative, we propose a hierarchical Bayesian approach, in which knowledge on the toxicity of chemicals other than those assessed is incorporated. A case study with a mixture of 13 pharmaceuticals demonstrates that this hierarchical approach results in more realistic estimations of the potentially affected fraction, as a result of reduced uncertainty in species sensitivity distributions for data-poor chemicals. |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 0013-936X |
| DOI: | 10.1021/acs.est.5b02651 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cef01debaaecebab479467a55254eadd https://doi.org/10.1021/acs.est.5b02651 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....cef01debaaecebab479467a55254eadd |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 0013936X |
|---|---|
| DOI: | 10.1021/acs.est.5b02651 |